Dataset includes overview text document (accepted version of manuscript) and tables, figures, and supplementary materials. Supplementary tables provide summary data underlying figures, as noted in the text. This dataset is associated with the following publication: Wehmas, L., A. Deangelo, S. Hester, B. Chorley, G. Carswell, G. Olson, M. George, J. Carter, S. Eldridge, A. Fisher, B. Vallanat, and C. Wood. Metabolic Disruption Early in Life is Associated With Latent Carcinogenic Activity of Dichloroacetic Acid in Mice. TOXICOLOGICAL SCIENCES. Society of Toxicology, 159(2): 354-365, (2017).

These spreadsheets contain the underlying data, calculations, and R code for the figures of the manuscript "Persistent gene expression and DNA methylation alterations linked to carcinogenic effects of dichloroacetic acid". The first tab of every spreadsheet contains descriptions of the data (metadata). For clarifying questions regarding the data, please contact Dr. Brian Chorley (EPA-ORD) at chorley.brian@epa.gov. If you require a review token for the sequencing datasets located in the GEO links (RNAseq and RRBS), please contact Dr. Chorley. This dataset is associated with the following publication: Carswell, G., J. Chamberlin, B. Bennett, P. Bushel, and B. Chorley. Persistent gene expression and DNA methylation alterations linked to carcinogenic effects of dichloroacetic acid. Frontiers in Oncology. Frontiers, Lausanne, SWITZERLAND, 14: 1389634, (2024).

Tables, Figures, and Supplemental Materials. This dataset is associated with the following publication: Hill III, T., M. Nelms, S. Edwards, M. Martin, R. Judson, C. Corton, and C. Wood. Negative Predictors of Carcinogenicity for Environmental Chemicals. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 155(1): 157-169, (2017).

Tables, Figures, and Supplemental Materials. This dataset is associated with the following publication: Hill III, T., M. Nelms, S. Edwards, M. Martin, R. Judson, C. Corton, and C. Wood. Negative Predictors of Carcinogenicity for Environmental Chemicals. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 155(1): 157-169, (2017).

Datasets used in RD-023418: Adverse Outcome Pathway-Driven Identification of Rat Hepatocarcinogens in Short-Term Assays. This dataset is associated with the following publication: Rooney, J., T. Hill, C. Qin, F. Sistare, and C. Corton. Adverse outcome pathway-driven identification of rat liver tumorigens in short-term assays. TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, USA, 356: 99-113, (2018).

Datasets used in RD-023418: Adverse Outcome Pathway-Driven Identification of Rat Hepatocarcinogens in Short-Term Assays. This dataset is associated with the following publication: Rooney, J., T. Hill, C. Qin, F. Sistare, and C. Corton. Adverse outcome pathway-driven identification of rat liver tumorigens in short-term assays. TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, USA, 356: 99-113, (2018).

Supplementary Files 1-15 contain the generated assay data that was used to establish BMAD and determine treatment effects. The tabbed spreadsheet data is formatted so that it can be directly analyzed, once converted to individual comma-separated values (.csv) files, using the R code provided in Supplementary File 16. Column headings are described in the supplemental file 'Metadata Glossary.docx'. This dataset is associated with the following publication: Angrish, M., C. McQueen, E. Hubal, M. Bruno, Y. Ge, and B. Chorley. Mechanistic Toxicity Tests Based on an Adverse Outcome Pathway Network for Hepatic Steatosis. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 159(1): 159-169, (2017).

Supplementary Files 1-15 contain the generated assay data that was used to establish BMAD and determine treatment effects. The tabbed spreadsheet data is formatted so that it can be directly analyzed, once converted to individual comma-separated values (.csv) files, using the R code provided in Supplementary File 16. Column headings are described in the supplemental file 'Metadata Glossary.docx'. This dataset is associated with the following publication: Angrish, M., C. McQueen, E. Hubal, M. Bruno, Y. Ge, and B. Chorley. Mechanistic Toxicity Tests Based on an Adverse Outcome Pathway Network for Hepatic Steatosis. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 159(1): 159-169, (2017).

Supplementary data for "Tia Tate, Grace Patlewicz, Imran Shah, A comparison of machine learning approaches for predicting hepatotoxicity potential using chemical structure and targeted transcriptomic data, Computational Toxicology, Volume 29, 2024, 100301, ISSN 2468-1113, https://doi.org/10.1016/j.comtox.2024.100301.". This dataset is associated with the following publication: Tate, T., G. Patlewicz, and I. Shah. A comparison of machine learning approaches for predicting hepatotoxicity potential using chemical structure and targeted transcriptomic data. Computational Toxicology. Elsevier B.V., Amsterdam, NETHERLANDS, 29: 100301, (2024).

Microarray experiments used in the study. This dataset is associated with the following publication: Corton, J., K. Korunes, J. Abedini, H. El-Masri, J. Brown, K. Friedman, Y. Liu, C. Martini, S. He, and J. Rooney. Thresholds Derived from Common Measures in Rat Studies are Predictive of Liver Tumorigenic Chemicals. TOXICOLOGIC PATHOLOGY. Society of Toxicology, RESTON, VA, 48(7): 857-874, (2020).